Database Systems : The Complete Book download from: http://infolab.stanford.edu/~ullman/dscb.html

1. CS145 Introduction
About CS145
Relational Model, Schemas, SQL
Semistructured Model, XML
1

2. Content of CS145
Design of databases.
E/R model, relational model,
semistructured model, XML, UML, ODL.
Database programming.
SQL, XPath, XQuery, Relational algebra,
Datalog.
Not DBMS implementation (that’s
CS245, 346, 347, sometimes CS345).
2

3. Textbook “Situation”
The closest text for the course is First
Course in Database Systems/3rd Edition.
But it won’t be available until Friday.
First 2 chapters available on-line.
You may prefer Database Systems:
Complete Book (also used in CS245) or
have FCDB/2nd E.
If so, we’ll give you a free copy of the major
additions in FCDB/3rd E.
3

4. Do You Know SQL?
Explain the difference between:
SELECT b
FROM R a b
5 20
WHERE a<10 OR a>=10; 10 30
and 20 40
… …
SELECT b
FROM R; R
4

5. And How About These?
SELECT a
FROM R, S
WHERE R.b = S.b;
SELECT a
FROM R
WHERE b IN (SELECT b FROM S);
5

6. Course Requirements
1. Project: a little eBay supported by a
database.
Individual.
Uses Stanford Oracle system.
2. Homeworks: Gradiance (automated)
and “challenge problems” (written).
3. Midterm and final.
6

7. Gradiance Homework System
Automatic, fast-feedback system for
taking you through standard homework
problems and verifying your knowledge.
Unusual: goal is to get 100% and learn.
Homework in CS145 is not a “mini-test.”
You try as many times as you like and get
help with each wrong answer.
7

8. Gradiance (GOAL) Access
To get your account, you need:
1. “Value-Pak” with any of the class texts, or
purchase on-line.
2. Class token: For FCDB/3e use 1B8B815E;
for other books use A5DDE704.
Details in the intro.html file.
Advice on using Gradiance:
www.gradiance.com/info.html
8

9. Interesting Stuff About Databases
It used to be about boring stuff:
employee records, bank records, etc.
Today, the field covers all the largest
sources of data, with many new ideas.
Web search.
Data mining.
Scientific and medical databases.
Integrating information.
9

10. More Interesting Stuff
Database programming centers around
limited programming languages.
Only area where non-Turing-complete
languages make sense.
Leads to very succinct programming, but
also to unique query-optimization problems
(CS346).
10

11. Still More …
You may not notice it, but databases
are behind almost everything you do on
the Web.
Google searches.
Queries at Amazon, eBay, etc.
11

12. And More…
Databases often have unique
concurrency-control problems (CS245,
CS347).
Many activities (transactions) at the
database at all times.
Must not confuse actions, e.g., two
withdrawals from the same account must
each debit the account.
12

13. What is a Data Model?
1. Mathematical representation of data.
Examples: relational model = tables;
semistructured model = trees/graphs.
2. Operations on data.
3. Constraints.
13

14. A Relation is a Table
Attributes
(column
headers) name manf
Tuples Winterbrew Pete’s
(rows) Bud Lite Anheuser-Busch
Beers
Relation
name
14

15. Schemas
Relation schema = relation name and
attribute list.
Optionally: types of attributes.
Example: Beers(name, manf) or
Beers(name: string, manf: string)
Database schema = set of all relation
schemas in the database.
Database = collection of relations.
15

16. Why Relations?
Very simple model.
Often matches how we think about
data.
Abstract model that underlies SQL, the
most important database language
today.
16

17. Our Running Example
Beers(name, manf) Bars
Bars(name, addr, license) Sells Frequents
Likes
Drinkers(name, addr, phone)
Beers Drinkers
Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Underline = key (tuples cannot have
the same value in all key attributes).
Excellent example of a constraint.
17

18. Database Schemas in SQL
SQL is primarily a query language, for
getting information from a database.
But SQL also includes a data-definition
component for describing database
schemas.
18

19. Creating (Declaring) a Relation
Simplest form is:
CREATE TABLE <name> (
<list of elements>
);
To delete a relation:
DROP TABLE <name>;
19

20. Elements of Table Declarations
Most basic element: an attribute and its
type.
The most common types are:
INT or INTEGER (synonyms).
REAL or FLOAT (synonyms).
CHAR(n ) = fixed-length string of n
characters.
VARCHAR(n ) = variable-length string of
up to n characters.
20

21. Example: Create Table
CREATE TABLE Sells (
bar CHAR(20),
beer VARCHAR(20),
price REAL
);
21

22. SQL Values
Integers and reals are represented as
you would expect.
Strings are too, except they require
single quotes.
Two single quotes = real quote, e.g.,
’Joe’’s Bar’.
Any value can be NULL.
22

23. Dates and Times
DATE and TIME are types in SQL.
The form of a date value is:
DATE ’yyyy-mm-dd’
Example: DATE ’2007-09-30’ for Sept.
30, 2007.
23

24. Times as Values
The form of a time value is:
TIME ’hh:mm:ss’
with an optional decimal point and
fractions of a second following.
Example: TIME ’15:30:02.5’ = two
and a half seconds after 3:30PM.
24

25. Declaring Keys
An attribute or list of attributes may be
declared PRIMARY KEY or UNIQUE.
Either says that no two tuples of the
relation may agree in all the attribute(s)
on the list.
There are a few distinctions to be
mentioned later.
25

26. Declaring Single-Attribute Keys
Place PRIMARY KEY or UNIQUE after the
type in the declaration of the attribute.
Example:
CREATE TABLE Beers (
name CHAR(20) UNIQUE,
manf CHAR(20)
);
26

27. Declaring Multiattribute Keys
A key declaration can also be another
element in the list of elements of a
CREATE TABLE statement.
This form is essential if the key consists
of more than one attribute.
May be used even for one-attribute keys.
27

28. Example: Multiattribute Key
The bar and beer together are the key for Sells:
CREATE TABLE Sells (
bar CHAR(20),
beer VARCHAR(20),
price REAL,
PRIMARY KEY (bar, beer)
);
28

29. PRIMARY KEY vs. UNIQUE
1. There can be only one PRIMARY KEY
for a relation, but several UNIQUE
attributes.
2. No attribute of a PRIMARY KEY can
ever be NULL in any tuple. But
attributes declared UNIQUE may have
NULL’s, and there may be several
tuples with NULL.
29

30. Semistructured Data
A data model based on trees.
Motivation: flexible representation of
data.
Motivation: sharing of documents
among systems and databases.
30

31. Graphs of Semistructured Data
Nodes = objects.
Arc labels (properties of objects).
Atomic values at leaf nodes (nodes with
no arcs out).
Flexibility: no restriction on:
Labels out of a node.
Number of successors with a given label.
31

32. Example: Data Graph
root Notice a
new kind
beer beer of data.
bar
manf manf prize
name A.B.
name
servedAt year award
Bud
M’lob 1995 Gold
name addr
Joe’s Maple The beer object
for Bud
The bar object
for Joe’s Bar
32

33. XML
XML = Extensible Markup Language.
While HTML uses tags for formatting
(e.g., “italic”), XML uses tags for
semantics (e.g., “this is an address”).
33

34. XML Documents
Start the document with a declaration,
surrounded by <?xml … ?> .
Typical:
<?xml version = “1.0” encoding
= “utf-8” ?>
Balance of document is a root tag
surrounding nested tags.
34

35. Tags
Tags, as in HTML, are normally open-
close pairs, as <FOO> … </FOO>.
Optional single tag <FOO/>.
Tags may be nested arbitrarily.
XML tags are case sensitive.
35

36. Example: an XML Document
<?xml version = “1.0” encoding = “utf-8” ?> A NAME
<BARS> subobject
<BAR><NAME>Joe’s Bar</NAME>
<BEER><NAME>Bud</NAME>
<PRICE>2.50</PRICE></BEER>
<BEER><NAME>Miller</NAME>
<PRICE>3.00</PRICE></BEER> A BEER
subobject
</BAR>
<BAR> …
</BARS>
36

37. Attributes
Like HTML, the opening tag in XML can
have attribute = value pairs.
Attributes also allow linking among
elements (discussed later).
37

38. Bars, Using Attributes
<?xml version = “1.0” encoding = “utf-8” ?>
<BARS>
<BAR name = “Joe’s Bar”>
<BEER name = “Bud” price = 2.50 />
<BEER name = “Miller” price = 3.00 />
</BAR>
<BAR> … name and Notice Beer elements
price are
</BARS> have only opening tags
attributes
with attributes.
38

39. DTD’s (Document Type Definitions)
A grammatical notation for describing
allowed use of tags.
Definition form:
<!DOCTYPE <root tag> [
<!ELEMENT <name>(<components>)>
. . . more elements . . .
]>
39

40. Example: DTD
A BARS object has
<!DOCTYPE BARS [ zero or more BAR’s
nested within.
<!ELEMENT BARS (BAR*)>
<!ELEMENT BAR (NAME, BEER+)> A BAR has one
<!ELEMENT NAME (#PCDATA)> NAME and one
or more BEER
<!ELEMENT BEER (NAME, PRICE)> subobjects.
<!ELEMENT PRICE (#PCDATA)>
A BEER has a
]> NAME and a
NAME and PRICE
are HTML text (“parsed PRICE.
character data”).
40

41. Attributes
Opening tags in XML can have
attributes.
In a DTD,
<!ATTLIST E . . . >
declares an attribute for element E,
along with its datatype.
41

42. Example: Attributes No closing
tag or
subelements
<!ELEMENT BEER EMPTY>
<!ATTLIST name CDATA #REQUIRED,
manf CDATA #IMPLIED>
Character Required = “must occur”;
string Implied = “optional
Example use:
<BEER name=“Bud” />
42